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Improved Protocol for the Production of the Low-Expression Eukaryotic Membrane Protein Human Aquaporin 2 in Pichia pastoris for Solid-State NMR

机译:在固态毕赤酵母中生产低表达真核膜蛋白人水通道蛋白2的改进的协议。

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摘要

Solid-state nuclear magnetic resonance (SSNMR) is a powerful biophysical technique for studies of membrane proteins; it requires the incorporation of isotopic labels into the sample. This is usually accomplished through over-expression of the protein of interest in a prokaryotic or eukaryotic host in minimal media, wherein all (or some) carbon and nitrogen sources are isotopically labeled. In order to obtain multi-dimensional NMR spectra with adequate signal-to-noise ratios suitable for in-depth analysis, one requires high yields of homogeneously structured protein. Some membrane proteins, such as human aquaporin 2 (hAQP2), exhibit poor expression, which can make producing a sample for SSNMR in an economic fashion extremely difficult, as growth in minimal media adds additional strain on expression hosts. We have developed an optimized growth protocol for eukaryotic membrane proteins in the methylotrophic yeast . Our new growth protocol uses the combination of sorbitol supplementation, higher cell density, and low temperature induction (LT-SEVIN), which increases the yield of full-length, isotopically labeled hAQP2 ten-fold. Combining mass spectrometry and SSNMR, we were able to determine the nature and the extent of post-translational modifications of the protein. The resultant protein can be functionally reconstituted into lipids and yields excellent resolution and spectral coverage when analyzed by two-dimensional SSNMR spectroscopy.
机译:固态核磁共振(SSNMR)是研究膜蛋白的强大生物物理技术。它需要将同位素标记掺入样品中。这通常是通过在基本培养基中过量表达目标蛋白在原核或真核宿主中完成的,其中所有(或部分)碳源和氮源都经过同位素标记。为了获得具有适合于深入分析的足够的信噪比的多维NMR光谱,人们需要高产量的均质结构蛋白。一些膜蛋白,例如人水通道蛋白2(hAQP2),表现出较差的表达,这使得以经济方式生产SSNMR样品非常困难,因为在基本培养基中的生长会增加表达宿主的菌株。我们已经为甲基营养酵母中的真核膜蛋白开发了优化的生长方案。我们的新生长方案结合了山梨糖醇补充,更高的细胞密度和低温诱导(LT-SEVIN)的组合,从而将全长,同位素标记的hAQP2的产量提高了十倍。结合质谱和SSNMR,我们能够确定蛋白质的性质和翻译后修饰的程度。当通过二维SSNMR光谱分析时,所得蛋白质可以在功能上重组为脂质,并产生出色的分辨率和光谱覆盖率。

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